105 algorithm-development-"Multiple" "NTNU Norwegian University of Science and Technology" PhD positions in Belgium
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to the development of digital twins of sloshing tanks and explore collective learning approaches where multiple systems share knowledge. The PhD will be carried out in joint collaboration between the Université Libre
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contribute to the development of digital twins of propellers and explore collective learning approaches, where multiple propellers cooperate for optimal flight control. The PhD will be carried out in joint
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of teaching and research, the FSTM seeks to generate and disseminate knowledge and train new generations of responsible citizens in order to better understand, explain and advance society and environment we
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consumption while guaranteeing optimal power production. You will work on the cutting edge of both wind energy and machine learning, two of the fastest growing scientific disciplines, to develop graph-based
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data through advanced ex-situ measurement technologies. The group’s ambition is to develop a robust framework for capturing high-quality data from their in-house hybrid additive-subtractive research
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set a course for the future – a future that you can help to shape. The EMAT research group at the Faculty of Science (University of Antwerp) is seeking to fill a PhD position on the development
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spatial distributions of active phases across multiple length scales. The PhD student will collaborate with international partners to study the evolution of crystalline and amorphous domains in the hybrid
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to perform the following tasks: Contribute to the development of a comprehensive channel model for the C-band direct-to-device (D2D) satellite communications in rural, semiurban and urban scenarios
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better The right place for IMPACT. SnT researchers engage in demand-driven projects. Through our Partnership Programme, we work on projects with more than 45 industry partners Multiple funding sources
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. You will work on the cutting edge of both wind energy and machine learning, two of the fastest growing scientific disciplines, to develop machine learning surrogates of wind energy systems. As newer